Today's Internet is populated by millions of users, each having access to hundreds of millions of “pages” of content over the World Wide Web (WWW). Vendors offering millions of on-line products and services also populate the Internet. With so much available information, and with so many products and services available on-line, it is becoming increasingly difficult for users to find information that best suits their needs. Two fundamental challenges occur. The first challenge is to extract from users their actual needs or objectives. The second challenge is to create a sufficiently detailed search of available information to locate goods or services that fulfill those needs or objectives, and then to package that information in a way that is easily understood and acted upon by users.
A limitation of prior art search facilities on the Internet is their focus on the execution of the search, and not on either understanding the user's objectives in searching, or in helping the user to formulate a search request. Search facilities merely carry out the user's direct request, tabulate the results, and present all of these results to the user. These search facilities are limited in that they do not incorporate User Profiles in formulating multiple search requests or perform multi-dimensional analysis on the search results to determine the best match to the user's original request. Additionally, typical prior art systems present the user with search results in a tabular fashion, instead of in a well organized, intuitively integrated display.
Various search engines, such as those found at http://www.Yahoo.com and http://www.Excite.com, allow users to refine their Internet searches through the use of Boolean operators. In addition to Boolean searches, other new methods and systems have enabled users to refine their searches so that less unwanted information is presented.
However, despite these advances, even the most narrowly drawn user's search may still result in hundreds of “hits” or search results. The user must then investigate all of these results to determine which result best answers the user's search. As a result of this burden, the users often settles on results that are not the best available to satisfy their needs.
U.S. Pat. No. 6,041,326 entitled “Method and System in a Computer Network for an Intelligent Search Engine” describes a method and system for limiting a search engine based upon the preferences of a user. User-defined preferences are applied through a plug-in program to limit the scope of searches, so that less unwanted information is delivered to the user. A drawback of this approach is that only a single user query or search is affected. Additionally, these techniques do not utilize User Preferences to reformulate the user's search request into more efficient requests. Additionally, these techniques do not operate on the results of multiple, related searches.
Many on-line vendors, aware of the difficulties that a user faces in finding a desired product or service on-line, have sought to improve a user's purchasing experience through the analysis of purchasing patterns for individual users, and across multiple users. By using this analysis, the vendor is able to generate recommendations, and present these recommendations to a user guiding their searches. However, this approach is limited in that it is specific to a single vendor. This approach does not help the user select among alternative vendor offerings. Furthermore, these analyses do not incorporate well-known purchasing characteristics such as seasonal dependencies. This is at least partly due to lack of sufficient data because of reliance on online-only behavioral information.
Additionally, the above-described approach does not enable the user to easily combine related products or services from different vendors. As an example, consider the process of booking reservations for a trip. This process may include making airline reservations, booking a hotel room, renting a car, making meal reservations, or planning entertainment. Today, some vendors work together to enable users to search across their collective offerings. As an example, Websites, such as http://www.Buy.com allow a user to book airline, hotel, and car rental reservations, offered from several vendors, from the same site. However, even when vendors take this approach, the user's product choices are restricted to those of the participating vendors.
Finally, many on-line Internet Service Providers offer their users access to a storage space in which to store a Personal Web page. Though highly desired by most users, these Personal Web pages can be cumbersome to create. It is especially difficult for the vast number of users with limited computer knowledge. Furthermore, these Web pages are generally static, and do not reflect changing behavior patterns, or changes in the preferences of a user.
It is an object of the present invention to provide a system and method to employ User Preferences and behavior patterns to reformulate a user's search request into one or more related search requests, and to then analyze the results of these multiple searches to provide an optimal response to the user.
It is another object of the present invention to provide a system and method to enable users to improve the process of selecting among alternative vendors' offerings, and to streamline the process of purchasing related products.
It is a further object of the present invention to provide a system and method to permit the automatic generation of a personalized interface, based upon User Preferences, which can be continuously and automatically modified without direct user intervention. This personalized interface may be automatically re-configured to accommodate various types of networks, or network interface devices. In a preferred embodiment, this interface may be a Personalized Web page, a voice interface, or any personalized interface (such as a Personal Digital Assistant (PDA)) dependent upon the client device used and the network accessed.